The STEREO mission has opened up a new frontier in our ability to track coronal mass ejections (CMEs) and indeed the solar wind from the Sun to the Earth. The STEREO coronagraphs, COR1 and 2, allow CMEs to be identified and tracked from ~2-15 solar radii, while the revolutionary Heliospheric Imager (HI) allows them to be tracked the whole way to the Earth. These advancements have only been possible due to recent developments in image processing and visualisation. In this talk, I will review a number of image processing techniques to enhance the visibility of features in COR 1 and 2 and HI. Furthermore, I will describe how the two perspectives of STEREO in conjunction with novel 3D image reconstruction methods can be used to better determine the morphology and kinematics of CMEs. Determining well-constrained kinematics of CMEs in the inner Heliosphere is crucial to making accurate estimates of their arrival times and space weather effects at Earth.

Coronal Bright Fronts (CBFs; commonly called "EIT waves'') are large scale wavefronts that propagate though the solar corona at hundreds of kilometres per second. Although spectacular, their physical nature and the exact nature of their relationship to CMEs remains a source of much debate. They are typically observed as bright diffuse features that are difficult to identify in individual images, with the current techniques used to study them producing highly user-defined results. To overcome this problem, a semi-automated technique has been developed that identifies, tracks and analyses EUV observations of CBFs. This technique is designed to work with minimal user input, allowing a self-consistent identification process and producing a statistically accurate estimate of the kinematics and morphological variation of the pulse. This will enable a systematic examination of the on-disk propagation of "EIT waves'', and allow their relationship to the erupting CME to be identified.

We present several advances in computational estimation of physical parameters in the solar corona. In particular, methods for both global dynamic estimation of coronal electron density and temperature, as well as estimation of local transient phenomena, such as coronal mass ejections, from empirical observations are described. Three-dimensional tomographic reconstructions of the solar corona from multiple points-of-view are obtained from instruments onboard the STEREO mission. Furthermore, a non-stationary formulation of the local reconstruction of transient phenomena from limited-angle projections is described which illustrates the potentials and challenges for imaging transient structures associated with space weather events from available observations.

For space weather applications, it is important to understand filaments evolution and especially their eruptions associated with coronal mass ejections. In view of the cadence and continuity of SDO observations, AIA and HMI offer a unique tool for such a program. Because of the data volume and the requirement of short latency, only an automated detection can be worked out. We present a new code for the automated detection and tracking of filaments, based on analysis of AIA 30.4 nm He II images and on the magnetic field measured by HMI. We discuss the algorithms and parameters that we use for filament detection, and we compare the efficiency and selectivity of this code with other filament detection codes. We finally discuss the possibility of using this code for detecting eruptions in real time.

As human endeavors and activities within the terrestrial atmosphere and beyond become increasingly vulnerable to extreme space-weather conditions, the need to reliably forecast these conditions becomes pressing. At least for eruptive solar flares and the related high-energy photon and energetic particulate, efficient forecasting means advance knowledge of flaring solar active regions before they actually flare. We now know, beyond reasonable doubt, that solar flares are of magnetic origin in complex, strong-field magnetic configurations. However, a prediction-oriented quantitative study of this magnetic complexity has proved problematic, both ambiguous and statistically infeasible, and this has clearly inhibited breakthrough progress in the forecasting front. In this presentation we focus on the physics of magnetic-complexity parameters in solar active regions and thereby assess what parameters should, and what should not, work in terms of flare forecasting. We further explain why it is likely for solar-flare prediction to remain inherently probabilistic. For a category of apparently more promising magnetic-complexity parameters we briefly discuss the challenges faced by ongoing efforts to adapt these parameters for use with line-of-sight or vector magnetic field data acquired by the newly launched Solar Dynamics Observatory.

Newly emerging magnetic fields in and around solar active regions are known to destabilize active region magnetic fields and thus trigger coronal mass ejections. Thus having an early-warning system for these events may be useful for space weather forecasting. The SWAMIS-EF emerging magnetic flux region detection module is running on near-real-time magnetograms in the data pipeline of the Solar Dynamics Observatory. We will present an overview of the algorithm and show some detailed observations of emerging flux around times of notable space weather events, such as the 2011 February 15 solar storms.

In this talk, recent advances in automated solar imaging, real-time large-scale data processing, machine learning and software development for space weather are discussed. Recent technologies developed at Bradford University have been used to provide operational flares prediction, large-scale processing and association of solar data, super-resolution images, 3D representation and modelling of solar features and loop and the generation of 2D/3D synoptic maps and butterfly models. The practical implementation of these technologies and some directions for future research will be discussed as well.

The emergence of a new Active Region (AR) on the Sun's disk is an event of Space Weather importance, typically detected via analysis of full-disk continuum images or line-of-sight magnetograms. It is generally assumed that current instrumentation allows good visibility of the emergence process. We present an automated detection technique that identifies AR emergence in line-of-sight magnetogram data. The technique, which uses morphological detection methods on difference images, is applied to the NSO Kitt Peak 512-channel magnetograph dataset, for the 20-year time range between 1974 and 1993. We obtain the distribution of locations of new emergences on the solar disk, and show that it has a strong asymmetry in longitude. There is an 11:1 ratio between the number of new regions seen to emerge in the [-60°,-40°] longitude bin and in the [+40°,+60°] longitude bin. A very large fraction of new ARs emerging in the West of the Sun go undetected in line-of-sight magnetograms. We discuss the causes of this phenomenon and its Space Weather implications.

The SWAP EUV imager onboard PROBA2 provides a non-stop stream of coronal EUV images at a cadence of typically 100s. These images show the solar drivers of space weather, such as flares and erupting filaments. We developed a software processing pipeline that automatically processes the images and localizes and identifies flares. Together with the sister instrument LYRA (a UV radiometer) we can also estimate the magnitude of the flares in the well known ABCMX scale of NOAA. With the combination of SWAP and LYRA, as small ESA instruments, and our software, we can provide an independent service to monitor flare activity. The output of this software is meant as a service to/from the Space Weather Segment of ESA's Space Situational Awareness Program. In this paper we will present the concept of the software pipeline, statistics on its success and the online display in real-time of its results.